SoroushVahidi/scidocs huggingface dataset:
A quadruped robot with parallel mechanism legs
(2014)

Summary form only given. The design and control of quadruped robots has become a fascinating research field because they have better mobility on unstructured terrains. Until now, many kinds of quadruped robots were developed, such as JROB-1 [1], BISAM [2], BigDog [3], LittleDog [4], HyQ [5] and Cheetah cub [6]. They have shown significant walking performance. However, most of them use serial mechanism legs and have animal like structure: the thigh and the crus. To swing the crus in swing phase and support the body's weight in stance phase, a linear actuator is attached on the thigh [2, 3, 5, 6], or instead, a rotational actuator is installed on the knee joint [1, 4]. To make the robot more useful in the wild environment, e.g., the detection or manipulation tasks, the payload capability is very important. To carry the sensors or tools, heavy load legged robot is very necessary. Thus the knee actuator should be lightweight, powerful and easy to maintain. However, this can be very costly and hard to satisfy at the same time.
An Overview of Inter-Vehicular Communication Systems, Protocols and Middleware
(2013)

Inter-vehicular communication is an important research area that is rapidly growing due to considerable advances in mobile and wireless communication technologies, as well as the growth of microprocessing capabilities inside today’s cars, and other moving vehicles. A good amount of research has been done to exploit the different services that can be provided to enhance the safety and comfort of the driver. Additional functions provide the car electronics and the passengers with access to the Internet and other core network resources. This paper provides a survey of the latest advances in the area of inter-vehicular communication (IVC) including vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) functions and services. In addition, the paper presents the most important projects and protocols that are involved in IVC systems as well as the different issues and challenges that exist at each layer of the networking model.
DERI&UPM: Pushing Corpus Based Relatedness to Similarity: Shared Task System Description
(2012)

In this paper, we describe our system submitted for the semantic textual similarity (STS) task at SemEval 2012. We implemented two approaches to calculate the degree of similarity between two sentences. First approach combines corpus-based semantic relatedness measure over the whole sentence with the knowledge-based semantic similarity scores obtained for the words falling under the same syntactic roles in both the sentences. We fed all these scores as features to machine learning models to obtain a single score giving the degree of similarity of the sentences. Linear Regression and Bagging models were used for this purpose. We used Explicit Semantic Analysis (ESA) as the corpus-based semantic relatedness measure. For the knowledgebased semantic similarity between words, a modified WordNet based Lin measure was used. Second approach uses a bipartite based method over the WordNet based Lin measure, without any modification. This paper shows a significant improvement in calculating the semantic similarity between sentences by the fusion of the knowledge-based similarity measure and the corpus-based relatedness measure against corpus based measure taken alone.
Creating Ground Truth for Historical Manuscripts with Document Graphs and Scribbling Interaction
(2016)

Ground truth is both - indispensable for training and evaluating document analysis methods, and yet very tedious to create manually. This especially holds true for complex historical manuscripts that exhibit challenging layouts with interfering and overlapping handwriting. In this paper, we propose a novel semi-automatic system to support layout annotations in such a scenario based on document graphs and a pen-based scribbling interaction. On the one hand, document graphs provide a sparse page representation that is already close to the desired ground truth and on the other hand, scribbling facilitates an efficient and convenient pen-based interaction with the graph. The performance of the system is demonstrated in the context of a newly introduced database of historical manuscripts with complex layouts.
Aletheia - An Advanced Document Layout and Text Ground-Truthing System for Production Environments
(2011)

Large-scale digitisation has led to a number of new possibilities with regard to adaptive and learning based methods in the field of Document Image Analysis and OCR. For ground truth production of large corpora, however, there is still a gap in terms of productivity. Ground truth is not only crucial for training and evaluation at the development stage of tools but also for quality assurance in the scope of production workflows for digital libraries. This paper describes Aletheia, an advanced system for accurate and yet cost-effective ground truthing of large amounts of documents. It aids the user with a number of automated and semi-automated tools which were partly developed and improved based on feedback from major libraries across Europe and from their digitisation service providers which are using the tool in a production environment. Novel features are, among others, the support of top-down ground truthing with sophisticated split and shrink tools as well as bottom-up ground truthing supporting the aggregation of lower-level elements to more complex structures. Special features have been developed to support working with the complexities of historical documents. The integrated rules and guidelines validator, in combination with powerful correction tools, enable efficient production of highly accurate ground truth.
LabelMe: A Database and Web-Based Tool for Image Annotation
(2005)

We seek to build a large collection of images with ground truth labels to be used for object detection and recognition research. Such data is useful for supervised learning and quantitative evaluation. To achieve this, we developed a web-based tool that allows easy image annotation and instant sharing of such annotations. Using this annotation tool, we have collected a large dataset that spans many object categories, often containing multiple instances over a wide variety of images. We quantify the contents of the dataset and compare against existing state of the art datasets used for object recognition and detection. Also, we show how to extend the dataset to automatically enhance object labels with WordNet, discover object parts, recover a depth ordering of objects in a scene, and increase the number of labels using minimal user supervision and images from the web.
Decoronation - a conservative method to treat ankylosed teeth for preservation of alveolar ridge prior to permanent prosthetic reconstruction: literature review and case presentation.
(2007)

Avulsed teeth that are stored extraorally in a dry environment for >60 min generally develop replacement root resorption or ankylosis following their replantation due to the absence of a vital periodontal ligament on their root surface. One negative sequelae of such ankylosis is tooth infra-positioning and the local arrest of alveolar bone growth. Removal of an ankylosed tooth may be difficult and traumatic leading to esthetic bony ridge deformities and optimal prosthetic treatment interferences. Recently a treatment option for ankylosed teeth named 'de-coronation' gained interest, particularly in pediatric dentistry that concentrated in dental traumatology. This article reviews the up-to-date literature that has been published on decoronation with respect to its importance for future prosthetic rehabilitation followed by a case presentation that demonstrates its clinical benefits.
A Component-Based Dynamic Link Support for Safety-Critical Embedded Systems
(2013)

Safety-critical embedded systems have to undergo rigorous development process in order to ensure that their function will not compromise humans or environment where they operate. Therefore, they rely on simple and proven-in-use design. However, with growing software complexity, maintenance becomes very important aspect in safety domain. Recent approaches for managing maintenance allow to perform changes on software at design-time, which implies that the whole system has to be rebuilt when the application software changes. In this paper, we describe more flexible solution for updating the application software. We apply the component-based paradigm to construct the application software, i.e. we define a model of a software function that can be dynamically linked with the entire operating system (OS). In order to avoid the usage of the OS-provided support for dynamic linking, we design software functions as position-independent and relocation-free binaries with well-defined interfaces. With the help of component-based paradigm we show how to simplify the link support and make it suitable for safety domain.
Data mining in software engineering
(2011)

The increased availability of data created as part of the sof tware development process allows us to apply novel analysis techniques on the data and use the results to guide t he process’s optimization. In this paper we describe variou s data sources and discuss the principles and techniques of data mi ning as applied on software engineering data. Data that can b e mined is generated by most parts of the development process: requi rements elicitation, development analysis, testing, debu gging, and maintenance. Based on this classification we survey the mini ng approaches that have been used and categorize them accord ing to the corresponding parts of the development process and th e task they assist. Thus the survey provides researchers wit h a concise overview of data mining techniques applied to softw are engineering data, and aids practitioners on the selecti on of appropriate data mining techniques for their work.
Signal Processing for FMCW SAR
(2007)

The combination of frequency-modulated continuous-wave (FMCW) technology and synthetic aperture radar (SAR) techniques leads to lightweight cost-effective imaging sensors of high resolution. One limiting factor to the use of FMCW sensors is the well-known presence of nonlinearities in the transmitted signal. This results in contrast- and range-resolution degradation, particularly when the system is intended for high-resolution long-range applications, as it is the case for SAR. This paper presents a novel processing solution, which solves the nonlinearity problem for the whole range profile. Additionally, the conventional stop-and-go approximation used in pulse-radar algorithms is not valid in FMCW SAR applications under certain circumstances. Therefore, the motion within the sweep needs to be taken into account. Analytical development of the FMCW SAR signal model, starting from the deramped signal and without using the stop-and-go approximation, is presented in this paper. The model is then applied to stripmap, spotlight, and single-transmitter/multiple-receiver digital-beamforming SAR operational mode. The proposed algorithms are verified by processing real FMCW SAR data collected with the demonstrator system built at the Delft University of Technology.
Air-Gap Convection in Rotating Electrical Machines
(2012)

This paper reviews the convective heat transfer within the air gap of both cylindrical and disk geometry rotating electrical machines, including worked examples relevant to fractional horsepower electrical machines. Thermal analysis of electrical machines is important because torque density is limited by maximum temperature. Knowledge of surface convective heat transfer coefficients is necessary for accurate thermal modeling, for example, using lumped parameter models. There exists a wide body of relevant literature, but much of it has traditionally been in other application areas, dominated by mechanical engineers, such as gas turbine design. Particular attention is therefore given to the explanation of the relevant nondimensional parameters and to the presentation of measured convective heat transfer correlations for a wide variety of situations from laminar to turbulent flow at small and large gap sizes for both radial-flux and axial-flux electrical machines.
CAPTCHA: Using Hard AI Problems for Security
(2003)

We introduce captcha, an automated test that humans can pass, but current computer programs can’t pass: any program that has high success over a captcha can be used to solve an unsolved Artificial Intelligence (AI) problem. We provide several novel constructions of captchas. Since captchas have many applications in practical security, our approach introduces a new class of hard problems that can be exploited for security purposes. Much like research in cryptography has had a positive impact on algorithms for factoring and discrete log, we hope that the use of hard AI problems for security purposes allows us to advance the field of Artificial Intelligence. We introduce two families of AI problems that can be used to construct captchas and we show that solutions to such problems can be used for steganographic communication. captchas based on these AI problem families, then, imply a win-win situation: either the problems remain unsolved and there is a way to differentiate humans from computers, or the problems are solved and there is a way to communicate covertly on some channels.
Multiple social identities and stereotype threat: imbalance, accessibility, and working memory.
(2009)

In 4 experiments, the authors showed that concurrently making positive and negative self-relevant stereotypes available about performance in the same ability domain can eliminate stereotype threat effects. Replicating past work, the authors demonstrated that introducing negative stereotypes about women's math performance activated participants' female social identity and hurt their math performance (i.e., stereotype threat) by reducing working memory. Moving beyond past work, it was also demonstrated that concomitantly presenting a positive self-relevant stereotype (e.g., college students are good at math) increased the relative accessibility of females' college student identity and inhibited their gender identity, eliminating attendant working memory deficits and contingent math performance decrements. Furthermore, subtle manipulations in questions presented in the demographic section of a math test eliminated stereotype threat effects that result from women reporting their gender before completing the test. This work identifies the motivated processes through which people's social identities became active in situations in which self-relevant stereotypes about a stigmatized group membership and a nonstigmatized group membership were available. In addition, it demonstrates the downstream consequences of this pattern of activation on working memory and performance.
Multiuser Resource Allocation for Mobile-Edge Computation Offloading
(2016)

Mobile-edge computation offloading (MECO) offloads intensive mobile computation to clouds located at the edges of cellular networks. Thereby, MECO is envisioned as a promising technique for prolonging the battery lives and enhancing the computation capacities of mobiles. In this paper, we consider resource allocation in a MECO system comprising multiple users that time share a single edge cloud and have different computation loads. The optimal resource allocation is formulated as a convex optimization problem for minimizing the weighted sum mobile energy consumption under constraint on computation latency and for both the cases of infinite and finite edge cloud computation capacities. The optimal policy is proved to have a threshold-based structure with respect to a derived offloading priority function, which yields priorities for users according to their channel gains and local computing energy consumption. As a result, users with priorities above and below a given threshold perform complete and minimum offloading, respectively. Computing the threshold requires iterative computation. To reduce the complexity, a sub-optimal resource-allocation algorithm is proposed and shown by simulation to have close-to-optimal performance.
Trimming and Improving Skip-thought Vectors
(2017)

The skip-thought model has been proven to be effective at learning sentence representations and capturing sentence semantics. In this paper, we propose a suite of techniques to trim and improve it. First, we validate a hypothesis that, given a current sentence, inferring the previous and inferring the next sentence provide similar supervision power, therefore only one decoder for predicting the next sentence is preserved in our trimmed skip-thought model. Second, we present a connection layer between encoder and decoder to help the model to generalize better on semantic relatedness tasks. Third, we found that a good word embedding initialization is also essential for learning better sentence representations. We train our model unsupervised on a large corpus with contiguous sentences, and then evaluate the trained model on 7 supervised tasks, which includes semantic relatedness, paraphrase detection, and text classification benchmarks. We empirically show that, our proposed model is a faster, lighter-weight and equally powerful alternative to the original skip-thought model.
Self-tuning fuzzy PID controller for electro-hydraulic cylinder
(2011)

Hydraulic systems are widely used in industrial applications. This is due to its high speed of response with fast start, stop and speed reversal possible. The torque to inertia ratio is also large with resulting high acceleration capability. The nonlinear properties of hydraulic cylinder make the position tracking control design challenging. This paper presents the development and implementation of self-tuning fuzzy PID controller in controlling the position variation of electro-hydraulic actuator. The hydraulic system mathematical model is approximated using system identification technique. The simulation studies were done using Matlab Simulink environment. The output performance was compared with the design using pole-placement controller. The roots mean squared error for both techniques showed that self-tuning Fuzzy PID produced better result compared to using pole-placement controller.
Formula Derivation and Verification of Characteristic Impedance for Offset Double-Sided Parallel Strip Line (DSPSL)
(2010)

Double-sided parallel strip line (DSPSL) is a versatile microwave transmission line. With an offset, it allows for large variations of the characteristic impedance and therefore flexibility for the design of novel microwave devices. In this letter, a formula for the characteristic impedance of DSPSL is derived by the fuzzy EM method and verified by commercial software. Very good agreement is observed.
Two Conceptions of the Physical
(2002)

The debate over physicalism in philosophy of mind can be seen as concerning an inconsistent tetrad of theses: (1) if physicalism is true, a priori physicalism is true; (2) a priori physicalism is false; (3) if physicalism is false, epiphenomenalism is true; (4) epiphenomenalism is false. This paper argues that one may resolve the debate by distinguishing two conceptions of the physical: on the theory-based conception, it is plausible that (2) is true and (3) is false; on the object-based conception, it is plausible that (3) is true and (2) is false. The paper also defends and explores the version of physicalism that results from this strategy. 1. One way to view the contemporary debate in philosophy of mind over physicalism is to see it as being organized around an inconsistent tetrad of theses. These are: (1) If physicalism is true, a priori physicalism is true. (2) A priori physicalism is false. (3) If physicalism is false, epiphenomenalism is true. (4) Epiphenomenalism is false. It is obvious of course that these theses are inconsistent: (1) and (2) entail that physicalism is false, while (3) and (4) entail that it is true. Barring ambiguity, therefore, one thing we know is that one of the theses is false. On the other hand, each of the theses has powerful considerations, or at least what seem initially to be powerful considerations, in its favor. (1) In support of (1) are considerations of supervenience, articulated most clearly in recent times by Frank Jackson and David Chalmers. A priori physicalism is a thesis with two parts. The first part-the physicalist part-is that the mental supervenes with metaphysical necessity on the physical. The second part-the a priori part-is that mental truths are a priori entailed by physical truths. Many philosophers hold that supervenience stands in need of justification or explanation; Jackson and Chalmers argue that the project of justifying or explaining supervenience just is the project of making it plausible that there is an a priori entailment of the mental by the physical. This suggests that the first part of
A modular architecture for building automation systems
(2006)

The deployment of building automation systems (BAS) allows to increase comfort, safety and security and to reduce operational cost. Today such systems typically follow a two-layered hierarchical approach. While control networks interconnect distributed sensors, actuators and controllers, a backbone provides the necessary infrastructure for management tasks hosted by configuration and management devices. In addition, devices interconnecting the control network with the backbone and the backbone with further networks (e.g., the Internet) play a strategic role. All BAS devices contributing to a particular functionality differ in their requirements for hardware. This paper discusses requirements for devices used in the building automation domain and presents our work in progress to assemble platforms with different purposes relying on a modular architecture.
Exploring actor-object relationships for query-focused multi-document summarization
(2015)

Most research on multi-document summarization explores methods that generate summaries based on queries regardless of the users’ preferences. We note that, different users can generate somewhat different summaries on the basis of the same source data and query. This paper presents our study on how to exploit the information regards how users summarized their texts. Models of different users can be used either separately, or in an ensemble-like fashion. Machine learning methods are explored in the construction of the individual models. However, we explore yet another hypothesis. We believe that the sentences selected into the summary should be coherent and supplement each other in their meaning. One method to model this relationship between sentences is by detecting actor–object relationship (AOR). The sentences that satisfy this relationship have their importance value enhanced. This paper combines ensemble summarizing system and AOR to generate summaries. We have evaluated this method on DUC 2006 and DUC 2007 using ROUGE measure. Experimental results show the supervised method that exploits the ensemble summarizing system combined with AOR outperforms previous models when considering performance in query-based multidocument summarization tasks. Keyword User-based summarization · Actor–object relationship · Multi-document summarization · Ensemble summarizing system · Training data construction Communicated by V. Loia. M. Valizadeh (B) · P. Brazdil LIAAD INESC Tec, University of Porto, Porto, Portugal e-mail: valizadehmr@gmail.com P. Brazdil FEP, University of Porto, Porto, Portugal e-mail: pbrazdil@inescporto.pt